4.7 Article

Urinary Microbial and Metabolomic Profiles in Kidney Stone Disease

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FRONTIERS MEDIA SA
DOI: 10.3389/fcimb.2022.953392

关键词

nephrolithiasis; metabolome; microbiome; biomarker; urine

资金

  1. Health system scientific research project of Guangming district, Shenzhen City
  2. Nation Key R&D Program of China
  3. [2020R01040]
  4. [2019YFC0121904]

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A study was conducted on urinary microbiome compositions and metabolic alterations in nephrolithiasis patients, revealing distinct profiles from healthy individuals. Potential diagnostic metabolites and differential metabolic pathways were identified, shedding new light on the disease pathogenesis and providing early clinical biomarkers for diagnosis.
BackgroundKidney stones or nephrolithiasis is a chronic metabolic disease characterized by renal colic and hematuria. Currently, a pathogenetic mechanism resulting in kidney stone formation remains elusive. We performed a multi-omic study investigating urinary microbial compositions and metabolic alterations during nephrolithiasis. MethodUrine samples from healthy and individuals with nephrolithiasis were collected for 16S rRNA gene sequencing and liquid chromatography-mass spectroscopy. Microbiome and metabolome profiles were analyzed individually and combined to construct interactome networks by bioinformatic analysis. ResultsDistinct urinary microbiome profiles were determined in nephrolithiasis patients compared with controls. Thirty-nine differentially abundant taxa between controls and nephrolithiasis patients were identified, and Streptococcus showed the most significant enrichment in nephrolithiasis patients. We also observed significantly different microbial compositions between female and male nephrolithiasis patients. The metabolomic analysis identified 112 metabolites that were differentially expressed. Two significantly enriched metabolic pathways, including biosynthesis of unsaturated fatty acids and tryptophan metabolism, were also identified in nephrolithiasis patients. Four potentially diagnostic metabolites were also identified, including trans-3-hydroxycotinine, pyroglutamic acid, O-desmethylnaproxen, and FAHFA (16:0/18:2), and could function as biomarkers for the early diagnosis of nephrolithiasis. We also identified three metabolites that contributed to kidney stone size. Finally, our integrative analysis of the urinary tract microbiome and metabolome identified distinctly different network characteristics between the two groups. ConclusionsOur study has characterized important profiles and correlations among urinary tract microbiomes and metabolomes in nephrolithiasis patients for the first time. These results shed new light on the pathogenesis of nephrolithiasis and could provide early clinical biomarkers for diagnosing the disease.

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